Designing Dynamic Reassignment Mechanisms: Evidence from GP Allocation

Many centralized assignment systems seek to not only provide good matches for participants’ current needs, but also to accommodate changing preferences and circumstances. We study the problem of designing such a mechanism in the context of Norway’s system for dynamically allocating patients to general practitioners (GPs). We provide direct evidence of misallocation under the current system––patients sitting on waitlists for each others’ GPs, but who cannot trade––and propose an alternative mechanism that adapts the Top-Trading Cycles (TTC) algorithm to a dynamic environment. Because of patients’ dynamic incentives, dynamic TTC raises novel incentive and distributional concerns relative to the static case. We then estimate a structural model of switching behavior and GP choice and empirically evaluate how this mechanism would perform relative to the status quo. While introducing TTC would on average reduce waiting times and increase patient welfare—with especially large benefits for young and female patients—patients endowed with undesirable GPs would be harmed. Adjustments to the priority system can avoid harming this group while preserving most of the gains from TTC.